FEBRUARY 2010
Michael Lamoureux – The doctor of Sourcing Innovation
Perspective -
A Brief History of Optimization
In The Beginning...
In the beginning, there was the reverse auction.
Industry visionaries applied reverse auctions to their
sourcing events for commodity and competitive
categories (in the mid nineties) and saved a small
fortune (which sometimes exceeded 30%, 50%, and
even 70% of previous category costs). They were
heroes and the world was good.
Then, a couple of years later when they circled back to the first categories and held another auction, something unexpected (to them) happened. The total savings shrunk considerably. The average savings, expressed in terms of percentages, dropped from the mid double digits to the (low) single digits. The savings often equalled what they would have expected from a traditional RFX / negotiation process. But the market was a seller’s market and the total event time, and thus the total event cost, was low, so with the right spin, they still looked quite successful. The world was still good.
In the mid nineties industry visionaries applied reverse auctions to their sourcing events and saved a small fortune. They were heroes and the world was good.
Another couple of years passed, and they circled back to the first categories again. But this time, the market was a buyer’s market again and savings were bound to equal those seen in the initial category reverse auctions, right? Wrong! Instead, something really surprising (to them) happened -- instead of saving money, total costs increased -- sometimes in the double digits! The world was a dark and scary place. What happened? Could it have been avoided?
What happened was arrogance and ignorance.
Before the mass-market acceptance of the internet
that began in the mid-nineties, three-bids-and-abuy
was the common practice as you usually only
knew of that many suppliers and getting multiple
bids was a very time consuming and difficult process.
As a result, the local suppliers knew they, more-orless,
had you, and your competition, captive and
that if they kept their prices relatively stable and
competitive, they got the business, no matter how
high their margins were. Then the internet opened
up access to a multitude of suppliers, some of whom
were very hungry for new business, and the reverse
auction allowed those suppliers who were hungriest to sacrifice margin for new business. As a result, those suppliers who had grown complacent in their belief that they could continue to charge margins of 50%, 100%, or more, found themselves in a quagmire when reverse auctions allowed newer, hungrier, suppliers to drop their margins to 30%, 20%, or less. On the flip side, the visionaries who ran the auctions saw huge price reductions for the first application in each category as they quickly squeezed the fat out of the supplier's margins in an open and transparent market.
However, once the supplier's margins were gone, they were gone. The suppliers couldn't go any lower on a price-per-unit cost with their anticipated cost structure and, as a result, their bids failed to decrease the next time around. Then commodity costs rose and the suppliers had to raise their prices too or risk going out of business. And buyers, blind to the fact that all a reverse auction does is take fat out of supplier's margins until the margins are gone, lost big time.
But it could have been avoided.
Shortly after reverse auctions hit the big time, a few visionary individuals realized that reverse auctions were not the panacea the early auction platform providers were making them out to be. They realized that margins were not the only opportunity for savings and that a new solution would be needed if cost reductions were going to be identified in a regular and sustainable manner.
For example, you save 10% on price by accepting product from a lower quality supplier who is in China instead of Mexico, but ....
And they were going to do something about it.
Back in 1999, the visionaries started putting together the companies that were going to change the way strategic sourcing was done. Based on optimization, the new platforms would allow a sourcing professional to select sustainable solutions with the lowest total cost of ownership, and not just with the lowest price per unit. These visionaries understood that the reality is that the lowest total cost also depended on the total transportation cost, the total import and export costs, the quality and utilization costs (which determined cost of waste and warranty support, for example), and so on. Unless you could simultaneously reduce, or at least hold steady, all of these other costs, a price reduction could actually cost you more money in the long run. (For example, you save 10% on price by accepting product from a lower quality supplier who is in China instead of Mexico, but then your transportation costs triple and your warranty service costs increase tenfold.)
Enter Optimization
A year later, in 2000, the first optimization platforms from companies like CombineNet, Emptoris, MindFlow, and Trade Extensions appeared. They were primitive at first, with initial releases from some providers not being able to support multiple items, not being able to support ship-to locations, not being able to support volume bids, or not being able to support multiple cost components (which means you had to specify the total landed cost or total ownership cost for each supplier, item, ship-to, and/or volume break combination, depending on what the solution supported). They were also fairly slow and very limited in terms of maximum model size, often not being able to handle more than a handful of suppliers, a few dozen items, and a few score of ship-to locations.
However, the solutions improved rapidly, and within three years a number of solutions not only supported multiple items, multiple suppliers, multiple ship to locations, and multiple volume breaks, but these solutions also supported product substitution, discounts on item groups, and qualitative constraints. The solvers behind the models also became significantly more powerful and could support hundreds of suppliers supplying thousands of items to thousands of locations, and solve the models in hours, and sometimes minutes.
And some platforms, like Trade Extensions, even build optimization into their reverse auctions so you can get the best of both worlds.
Optimization Turns Ten
This year, strategic sourcing decision optimization, which is still considered the new kid on the sourcing platform block, turns ten and I have to say that it's grown up fast. Today's platforms now also support arbitrary discount groupings by supplier, unlimited cost factors with a total cost of ownership defined as a formula across those cost factors, simultaneous make-vs-buy analysis, constraints defined on user defined attribute groupings (suppliers in the North East, products with aluminum, etc.), and a host of other features. And some platforms, like Trade Extensions, even build optimization into their reverse auctions so you can get the best of both worlds. The maximum model size is enormous compared to what could be solved ten years ago. Consider the recent event run by a financial services company on 65,000 items and 60,000 transport destinations which involved over 400,000 bids from over 100 suppliers (and was valued at over 1 Billion Dollars). That's at least 1000 times larger than the largest model I would have attempted to solve ten years ago, and about as large as a real world sourcing model can get.
So please join me in wishing strategic sourcing decision optimization happy birthday. It's come a long way in a brief amount of time. As one of the early adopters, I’m sure you’ve seen, and continue to see, new benefits. Even though strategic sourcing decision optimization turns ten this year, my estimate is that still less than 10% of potential beneficiaries are using this technology. When you factor in all of the providers and resellers of sourcing platforms out there today, only 10% (or so) of these sourcing solution providers offer true strategic sourcing decision optimization, and at many of the suite providers who do offer this technology, only 10% to 20% of their customers take advantage of the power this solution has to offer.
Contributed by Michael Lamoureux, the doctor of Sourcing Innovation (http://blog.sourcinginnovation.com) a leading sourcing, procurement, and supply management blog read daily by practitioners around the globe.
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